PURPOSE: We sought to examine issues of generalizability in research on adolescent and young adult (AYA) cancer survivorship that relies on using community-based healthcare delivery system data. METHODS: Individuals aged 15 to 39 diagnosed with cancer between 1992 and 2006 were identified using data from community-based healthcare systems in California and Seattle. Loss to follow-up was defined as the first disenrollment (the end) of membership in the healthcare systems after cancer. Censoring occurred at death or study end (2009). We used Kaplan-Meier analysis to quantify follow-up, and multiple Cox regression to examine the association of follow-up loss with demographic and cancer characteristics. RESULTS: Of 6828 eligible AYAs, most (93%) were aged between 20 and 39 years at diagnosis; 62% were female and 39% were non-White. Solid tumors accounted for 81% of diagnoses. The majority (89%) of patients continued to be members of the healthcare systems and available for follow-up 1 year after diagnosis. Approximately 60% remained enrolled 5 years after diagnosis. Loss to follow-up was associated with younger age at diagnosis, male gender, and African American or Hispanic race/ethnicity. CONCLUSION: Data from community-based healthcare delivery systems offer an efficient way to identify large and diverse samples of AYA-onset cancer survivors. Differential loss to follow-up can threaten the generalizability of results from these studies and should be assessed quantitatively. Healthcare system data offer an alternative to studies requiring direct contact with participants.
PURPOSE: We sought to examine issues of generalizability in research on adolescent and young adult (AYA) cancer survivorship that relies on using community-based healthcare delivery system data. METHODS: Individuals aged 15 to 39 diagnosed with cancer between 1992 and 2006 were identified using data from community-based healthcare systems in California and Seattle. Loss to follow-up was defined as the first disenrollment (the end) of membership in the healthcare systems after cancer. Censoring occurred at death or study end (2009). We used Kaplan-Meier analysis to quantify follow-up, and multiple Cox regression to examine the association of follow-up loss with demographic and cancer characteristics. RESULTS: Of 6828 eligible AYAs, most (93%) were aged between 20 and 39 years at diagnosis; 62% were female and 39% were non-White. Solid tumors accounted for 81% of diagnoses. The majority (89%) of patients continued to be members of the healthcare systems and available for follow-up 1 year after diagnosis. Approximately 60% remained enrolled 5 years after diagnosis. Loss to follow-up was associated with younger age at diagnosis, male gender, and African American or Hispanic race/ethnicity. CONCLUSION: Data from community-based healthcare delivery systems offer an efficient way to identify large and diverse samples of AYA-onset cancer survivors. Differential loss to follow-up can threaten the generalizability of results from these studies and should be assessed quantitatively. Healthcare system data offer an alternative to studies requiring direct contact with participants.
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